Overview

Dataset statistics

Number of variables47
Number of observations1633
Missing cells39466
Missing cells (%)51.4%
Total size in memory599.7 KiB
Average record size in memory376.1 B

Variable types

Text37
Numeric10

Alerts

height_wo_shoes has 58 (3.6%) missing valuesMissing
height_wo_shoes_ft_in has 58 (3.6%) missing valuesMissing
height_w_shoes has 428 (26.2%) missing valuesMissing
height_w_shoes_ft_in has 428 (26.2%) missing valuesMissing
weight has 59 (3.6%) missing valuesMissing
wingspan has 58 (3.6%) missing valuesMissing
wingspan_ft_in has 58 (3.6%) missing valuesMissing
standing_reach has 59 (3.6%) missing valuesMissing
standing_reach_ft_in has 59 (3.6%) missing valuesMissing
body_fat_pct has 357 (21.9%) missing valuesMissing
hand_length has 794 (48.6%) missing valuesMissing
hand_width has 794 (48.6%) missing valuesMissing
standing_vertical_leap has 237 (14.5%) missing valuesMissing
max_vertical_leap has 237 (14.5%) missing valuesMissing
lane_agility_time has 246 (15.1%) missing valuesMissing
modified_lane_agility_time has 1124 (68.8%) missing valuesMissing
three_quarter_sprint has 246 (15.1%) missing valuesMissing
bench_press has 538 (32.9%) missing valuesMissing
spot_fifteen_corner_left has 1529 (93.6%) missing valuesMissing
spot_fifteen_break_left has 1527 (93.5%) missing valuesMissing
spot_fifteen_top_key has 1527 (93.5%) missing valuesMissing
spot_fifteen_break_right has 1527 (93.5%) missing valuesMissing
spot_fifteen_corner_right has 1527 (93.5%) missing valuesMissing
spot_college_corner_left has 1341 (82.1%) missing valuesMissing
spot_college_break_left has 1462 (89.5%) missing valuesMissing
spot_college_top_key has 1462 (89.5%) missing valuesMissing
spot_college_break_right has 1462 (89.5%) missing valuesMissing
spot_college_corner_right has 1462 (89.5%) missing valuesMissing
spot_nba_corner_left has 1381 (84.6%) missing valuesMissing
spot_nba_break_left has 1381 (84.6%) missing valuesMissing
spot_nba_top_key has 1381 (84.6%) missing valuesMissing
spot_nba_break_right has 1381 (84.6%) missing valuesMissing
spot_nba_corner_right has 1381 (84.6%) missing valuesMissing
off_drib_fifteen_break_left has 1432 (87.7%) missing valuesMissing
off_drib_fifteen_top_key has 1432 (87.7%) missing valuesMissing
off_drib_fifteen_break_right has 1432 (87.7%) missing valuesMissing
off_drib_college_break_left has 1483 (90.8%) missing valuesMissing
off_drib_college_top_key has 1602 (98.1%) missing valuesMissing
off_drib_college_break_right has 1602 (98.1%) missing valuesMissing
on_move_fifteen has 1449 (88.7%) missing valuesMissing
on_move_college has 1465 (89.7%) missing valuesMissing
bench_press has 40 (2.4%) zerosZeros

Reproduction

Analysis started2023-07-13 14:07:20.191597
Analysis finished2023-07-13 14:07:20.571767
Duration0.38 seconds
Software versionydata-profiling vv4.3.1
Download configurationconfig.json

Variables

season
Text

Distinct24
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:20.676869image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters6532
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2000
2nd row2000
3rd row2000
4th row2000
5th row2000
ValueCountFrequency (%)
2022 83
 
5.1%
2002 82
 
5.0%
2023 81
 
5.0%
2004 81
 
5.0%
2005 81
 
5.0%
2003 78
 
4.8%
2001 78
 
4.8%
2007 77
 
4.7%
2019 77
 
4.7%
2006 76
 
4.7%
Other values (14) 839
51.4%
2023-07-13T22:07:20.964134image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2535
38.8%
2 2142
32.8%
1 816
 
12.5%
3 222
 
3.4%
8 145
 
2.2%
7 141
 
2.2%
5 139
 
2.1%
4 137
 
2.1%
6 132
 
2.0%
9 123
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6532
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2535
38.8%
2 2142
32.8%
1 816
 
12.5%
3 222
 
3.4%
8 145
 
2.2%
7 141
 
2.2%
5 139
 
2.1%
4 137
 
2.1%
6 132
 
2.0%
9 123
 
1.9%

Most occurring scripts

ValueCountFrequency (%)
Common 6532
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2535
38.8%
2 2142
32.8%
1 816
 
12.5%
3 222
 
3.4%
8 145
 
2.2%
7 141
 
2.2%
5 139
 
2.1%
4 137
 
2.1%
6 132
 
2.0%
9 123
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6532
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2535
38.8%
2 2142
32.8%
1 816
 
12.5%
3 222
 
3.4%
8 145
 
2.2%
7 141
 
2.2%
5 139
 
2.1%
4 137
 
2.1%
6 132
 
2.0%
9 123
 
1.9%
Distinct1591
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:21.525581image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length7
Mean length5.916105328
Min length2

Characters and Unicode

Total characters9661
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1552 ?
Unique (%)95.0%

Sample

1st row2124
2nd row12019
3rd row12020
4th row12131
5th row2056
ValueCountFrequency (%)
1 5
 
0.3%
1629674 2
 
0.1%
1629617 2
 
0.1%
1629653 2
 
0.1%
1629670 2
 
0.1%
1631159 2
 
0.1%
1628417 2
 
0.1%
1631218 2
 
0.1%
1628981 2
 
0.1%
1629007 2
 
0.1%
Other values (1581) 1610
98.6%
2023-07-13T22:07:21.924379image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1978
20.5%
2 1918
19.9%
0 1212
12.5%
6 1116
11.6%
3 776
 
8.0%
9 578
 
6.0%
7 574
 
5.9%
4 541
 
5.6%
5 489
 
5.1%
8 474
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9656
99.9%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1978
20.5%
2 1918
19.9%
0 1212
12.6%
6 1116
11.6%
3 776
 
8.0%
9 578
 
6.0%
7 574
 
5.9%
4 541
 
5.6%
5 489
 
5.1%
8 474
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9661
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1978
20.5%
2 1918
19.9%
0 1212
12.5%
6 1116
11.6%
3 776
 
8.0%
9 578
 
6.0%
7 574
 
5.9%
4 541
 
5.6%
5 489
 
5.1%
8 474
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9661
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1978
20.5%
2 1918
19.9%
0 1212
12.5%
6 1116
11.6%
3 776
 
8.0%
9 578
 
6.0%
7 574
 
5.9%
4 541
 
5.6%
5 489
 
5.1%
8 474
 
4.9%
Distinct855
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:22.205685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length15
Median length10
Mean length5.422535211
Min length2

Characters and Unicode

Total characters8855
Distinct characters57
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique583 ?
Unique (%)35.7%

Sample

1st rowMalik
2nd rowHarold
3rd rowLamont
4th rowMario
5th rowPrimoz
ValueCountFrequency (%)
chris 24
 
1.5%
marcus 22
 
1.3%
jordan 19
 
1.2%
michael 17
 
1.0%
james 17
 
1.0%
brandon 16
 
1.0%
jalen 15
 
0.9%
isaiah 14
 
0.9%
josh 14
 
0.9%
justin 13
 
0.8%
Other values (843) 1463
89.5%
2023-07-13T22:07:22.537774image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 941
 
10.6%
e 888
 
10.0%
n 737
 
8.3%
r 692
 
7.8%
i 550
 
6.2%
o 516
 
5.8%
l 388
 
4.4%
s 344
 
3.9%
J 302
 
3.4%
y 266
 
3.0%
Other values (47) 3231
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7077
79.9%
Uppercase Letter 1720
 
19.4%
Other Punctuation 54
 
0.6%
Dash Punctuation 3
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 941
13.3%
e 888
12.5%
n 737
10.4%
r 692
9.8%
i 550
 
7.8%
o 516
 
7.3%
l 388
 
5.5%
s 344
 
4.9%
y 266
 
3.8%
h 246
 
3.5%
Other values (16) 1509
21.3%
Uppercase Letter
ValueCountFrequency (%)
J 302
17.6%
D 168
9.8%
M 163
9.5%
T 130
 
7.6%
C 118
 
6.9%
A 110
 
6.4%
R 104
 
6.0%
K 100
 
5.8%
S 86
 
5.0%
B 77
 
4.5%
Other values (16) 362
21.0%
Other Punctuation
ValueCountFrequency (%)
. 42
77.8%
' 10
 
18.5%
? 2
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8797
99.3%
Common 58
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 941
 
10.7%
e 888
 
10.1%
n 737
 
8.4%
r 692
 
7.9%
i 550
 
6.3%
o 516
 
5.9%
l 388
 
4.4%
s 344
 
3.9%
J 302
 
3.4%
y 266
 
3.0%
Other values (42) 3173
36.1%
Common
ValueCountFrequency (%)
. 42
72.4%
' 10
 
17.2%
- 3
 
5.2%
? 2
 
3.4%
1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8855
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 941
 
10.6%
e 888
 
10.0%
n 737
 
8.3%
r 692
 
7.8%
i 550
 
6.2%
o 516
 
5.8%
l 388
 
4.4%
s 344
 
3.9%
J 302
 
3.4%
y 266
 
3.0%
Other values (47) 3231
36.5%
Distinct1104
Distinct (%)67.6%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:22.807663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length18
Median length15
Mean length6.553582364
Min length0

Characters and Unicode

Total characters10702
Distinct characters58
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique891 ?
Unique (%)54.6%

Sample

1st rowAllen
2nd rowArceneaux
3rd rowBarnes
4th rowBland
5th rowBrezec
ValueCountFrequency (%)
williams 30
 
1.8%
jr 25
 
1.5%
brown 24
 
1.4%
johnson 21
 
1.3%
jones 20
 
1.2%
smith 19
 
1.1%
jackson 15
 
0.9%
green 12
 
0.7%
robinson 12
 
0.7%
thomas 10
 
0.6%
Other values (1079) 1488
88.8%
2023-07-13T22:07:23.139503image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 960
 
9.0%
n 850
 
7.9%
a 829
 
7.7%
o 809
 
7.6%
r 782
 
7.3%
i 651
 
6.1%
s 636
 
5.9%
l 626
 
5.8%
t 399
 
3.7%
h 275
 
2.6%
Other values (48) 3885
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8838
82.6%
Uppercase Letter 1761
 
16.5%
Space Separator 44
 
0.4%
Other Punctuation 31
 
0.3%
Dash Punctuation 24
 
0.2%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 960
10.9%
n 850
9.6%
a 829
9.4%
o 809
9.2%
r 782
 
8.8%
i 651
 
7.4%
s 636
 
7.2%
l 626
 
7.1%
t 399
 
4.5%
h 275
 
3.1%
Other values (16) 2021
22.9%
Uppercase Letter
ValueCountFrequency (%)
B 170
 
9.7%
M 151
 
8.6%
H 140
 
8.0%
S 138
 
7.8%
W 130
 
7.4%
J 121
 
6.9%
C 112
 
6.4%
D 81
 
4.6%
G 80
 
4.5%
P 79
 
4.5%
Other values (15) 559
31.7%
Other Punctuation
ValueCountFrequency (%)
. 26
83.9%
' 4
 
12.9%
? 1
 
3.2%
Space Separator
ValueCountFrequency (%)
44
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10599
99.0%
Common 103
 
1.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 960
 
9.1%
n 850
 
8.0%
a 829
 
7.8%
o 809
 
7.6%
r 782
 
7.4%
i 651
 
6.1%
s 636
 
6.0%
l 626
 
5.9%
t 399
 
3.8%
h 275
 
2.6%
Other values (41) 3782
35.7%
Common
ValueCountFrequency (%)
44
42.7%
. 26
25.2%
- 24
23.3%
' 4
 
3.9%
( 2
 
1.9%
) 2
 
1.9%
? 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10702
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 960
 
9.0%
n 850
 
7.9%
a 829
 
7.7%
o 809
 
7.6%
r 782
 
7.3%
i 651
 
6.1%
s 636
 
5.9%
l 626
 
5.8%
t 399
 
3.7%
h 275
 
2.6%
Other values (48) 3885
36.3%
Distinct1589
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:23.455801image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length22
Mean length12.97611758
Min length5

Characters and Unicode

Total characters21190
Distinct characters59
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1545 ?
Unique (%)94.6%

Sample

1st rowMalik Allen
2nd rowHarold Arceneaux
3rd rowLamont Barnes
4th rowMario Bland
5th rowPrimoz Brezec
ValueCountFrequency (%)
williams 30
 
0.9%
jr 26
 
0.8%
chris 24
 
0.7%
brown 24
 
0.7%
james 23
 
0.7%
marcus 23
 
0.7%
jordan 22
 
0.7%
johnson 21
 
0.6%
jones 20
 
0.6%
smith 19
 
0.6%
Other values (1867) 3078
93.0%
2023-07-13T22:07:23.832727image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1848
 
8.7%
a 1770
 
8.4%
1678
 
7.9%
n 1587
 
7.5%
r 1474
 
7.0%
o 1325
 
6.3%
i 1201
 
5.7%
l 1014
 
4.8%
s 980
 
4.6%
t 630
 
3.0%
Other values (49) 7683
36.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15915
75.1%
Uppercase Letter 3481
 
16.4%
Space Separator 1678
 
7.9%
Other Punctuation 85
 
0.4%
Dash Punctuation 27
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1848
11.6%
a 1770
11.1%
n 1587
10.0%
r 1474
9.3%
o 1325
 
8.3%
i 1201
 
7.5%
l 1014
 
6.4%
s 980
 
6.2%
t 630
 
4.0%
h 521
 
3.3%
Other values (16) 3565
22.4%
Uppercase Letter
ValueCountFrequency (%)
J 423
 
12.2%
M 314
 
9.0%
D 249
 
7.2%
B 247
 
7.1%
C 230
 
6.6%
S 224
 
6.4%
T 197
 
5.7%
R 178
 
5.1%
A 176
 
5.1%
H 159
 
4.6%
Other values (16) 1084
31.1%
Other Punctuation
ValueCountFrequency (%)
. 68
80.0%
' 14
 
16.5%
? 3
 
3.5%
Space Separator
ValueCountFrequency (%)
1678
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 19396
91.5%
Common 1794
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1848
 
9.5%
a 1770
 
9.1%
n 1587
 
8.2%
r 1474
 
7.6%
o 1325
 
6.8%
i 1201
 
6.2%
l 1014
 
5.2%
s 980
 
5.1%
t 630
 
3.2%
h 521
 
2.7%
Other values (42) 7046
36.3%
Common
ValueCountFrequency (%)
1678
93.5%
. 68
 
3.8%
- 27
 
1.5%
' 14
 
0.8%
? 3
 
0.2%
( 2
 
0.1%
) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21190
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1848
 
8.7%
a 1770
 
8.4%
1678
 
7.9%
n 1587
 
7.5%
r 1474
 
7.0%
o 1325
 
6.3%
i 1201
 
5.7%
l 1014
 
4.8%
s 980
 
4.6%
t 630
 
3.0%
Other values (49) 7683
36.3%
Distinct14
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:23.941103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.755664421
Min length0

Characters and Unicode

Total characters4500
Distinct characters6
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPF-C
2nd rowSG-SF
3rd rowPF-C
4th rowPF
5th rowC
ValueCountFrequency (%)
pf 289
17.8%
pg 263
16.2%
sg 239
14.7%
sf 194
11.9%
c 135
8.3%
sg-sf 95
 
5.8%
pf-c 83
 
5.1%
pg-sg 63
 
3.9%
sf-pf 62
 
3.8%
c-pf 62
 
3.8%
Other values (3) 143
8.8%
2023-07-13T22:07:24.091983image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
F 1005
22.3%
S 939
20.9%
P 917
20.4%
G 851
18.9%
- 508
11.3%
C 280
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3992
88.7%
Dash Punctuation 508
 
11.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F 1005
25.2%
S 939
23.5%
P 917
23.0%
G 851
21.3%
C 280
 
7.0%
Dash Punctuation
ValueCountFrequency (%)
- 508
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3992
88.7%
Common 508
 
11.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
F 1005
25.2%
S 939
23.5%
P 917
23.0%
G 851
21.3%
C 280
 
7.0%
Common
ValueCountFrequency (%)
- 508
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
F 1005
22.3%
S 939
20.9%
P 917
20.4%
G 851
18.9%
- 508
11.3%
C 280
 
6.2%

height_wo_shoes
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)4.8%
Missing58
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean77.60044444
Minimum67.75
Maximum89.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:24.160137image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum67.75
5-th percentile71.75
Q175.25
median77.75
Q380.125
95-th percentile82.5
Maximum89.25
Range21.5
Interquartile range (IQR)4.875

Descriptive statistics

Standard deviation3.356326849
Coefficient of variation (CV)0.04325138693
Kurtosis-0.301848243
Mean77.60044444
Median Absolute Deviation (MAD)2.5
Skewness-0.2289663092
Sum122220.7
Variance11.26492992
MonotonicityNot monotonic
2023-07-13T22:07:24.218036image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
76.5 53
 
3.2%
79 51
 
3.1%
79.25 51
 
3.1%
78 50
 
3.1%
80.75 49
 
3.0%
76 49
 
3.0%
77.75 46
 
2.8%
80.25 44
 
2.7%
78.5 44
 
2.7%
79.5 44
 
2.7%
Other values (65) 1094
67.0%
(Missing) 58
 
3.6%
ValueCountFrequency (%)
67.75 1
 
0.1%
68 1
 
0.1%
68.25 1
 
0.1%
68.75 3
0.2%
69 3
0.2%
ValueCountFrequency (%)
89.25 1
 
0.1%
87.5 1
 
0.1%
87.25 1
 
0.1%
85.75 1
 
0.1%
85.25 7
0.4%

height_wo_shoes_ft_in
Text

MISSING 

Distinct151
Distinct (%)9.6%
Missing58
Missing (%)3.6%
Memory size12.9 KiB
2023-07-13T22:07:24.406583image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.101587302
Min length6

Characters and Unicode

Total characters12760
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)2.7%

Sample

1st row6' 8.25''
2nd row6' 4.5''
3rd row6' 8.5''
4th row6' 5.5''
5th row7' 0.75''
ValueCountFrequency (%)
6 1394
45.9%
5 108
 
3.6%
7 73
 
2.4%
8.75 51
 
1.7%
7.25 49
 
1.6%
5.25 45
 
1.5%
6.25 43
 
1.4%
8.25 42
 
1.4%
9 40
 
1.3%
4 39
 
1.3%
Other values (114) 1156
38.0%
2023-07-13T22:07:24.669676image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 4725
37.0%
6 1635
 
12.8%
1465
 
11.5%
5 1384
 
10.8%
. 1204
 
9.4%
7 566
 
4.4%
2 484
 
3.8%
1 353
 
2.8%
0 334
 
2.6%
8 175
 
1.4%
Other values (3) 435
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 5929
46.5%
Decimal Number 5366
42.1%
Space Separator 1465
 
11.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1635
30.5%
5 1384
25.8%
7 566
 
10.5%
2 484
 
9.0%
1 353
 
6.6%
0 334
 
6.2%
8 175
 
3.3%
4 172
 
3.2%
9 133
 
2.5%
3 130
 
2.4%
Other Punctuation
ValueCountFrequency (%)
' 4725
79.7%
. 1204
 
20.3%
Space Separator
ValueCountFrequency (%)
1465
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12760
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
' 4725
37.0%
6 1635
 
12.8%
1465
 
11.5%
5 1384
 
10.8%
. 1204
 
9.4%
7 566
 
4.4%
2 484
 
3.8%
1 353
 
2.8%
0 334
 
2.6%
8 175
 
1.4%
Other values (3) 435
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 4725
37.0%
6 1635
 
12.8%
1465
 
11.5%
5 1384
 
10.8%
. 1204
 
9.4%
7 566
 
4.4%
2 484
 
3.8%
1 353
 
2.8%
0 334
 
2.6%
8 175
 
1.4%
Other values (3) 435
 
3.4%

height_w_shoes
Real number (ℝ)

MISSING 

Distinct85
Distinct (%)7.1%
Missing428
Missing (%)26.2%
Infinite0
Infinite (%)0.0%
Mean78.78896266
Minimum69
Maximum91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:24.744086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum69
5-th percentile73
Q176.5
median79
Q381.25
95-th percentile83.75
Maximum91
Range22
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation3.301766139
Coefficient of variation (CV)0.04190645527
Kurtosis-0.26888482
Mean78.78896266
Median Absolute Deviation (MAD)2.25
Skewness-0.194735774
Sum94940.7
Variance10.90165964
MonotonicityNot monotonic
2023-07-13T22:07:24.802669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80.5 49
 
3.0%
79.5 40
 
2.4%
79 38
 
2.3%
78 37
 
2.3%
78.75 35
 
2.1%
77.5 34
 
2.1%
81.5 34
 
2.1%
80.75 34
 
2.1%
80 34
 
2.1%
77.75 33
 
2.0%
Other values (75) 837
51.3%
(Missing) 428
26.2%
ValueCountFrequency (%)
69 1
0.1%
69.5 1
0.1%
69.75 1
0.1%
70 1
0.1%
70.25 2
0.1%
ValueCountFrequency (%)
91 1
 
0.1%
87.25 1
 
0.1%
87 1
 
0.1%
86.75 1
 
0.1%
86.5 4
0.2%

height_w_shoes_ft_in
Text

MISSING 

Distinct145
Distinct (%)12.0%
Missing428
Missing (%)26.2%
Memory size12.9 KiB
2023-07-13T22:07:24.946913image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.138589212
Min length6

Characters and Unicode

Total characters9807
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)3.7%

Sample

1st row6' 4.25''
2nd row6' 8.25''
3rd row5' 9.75''
4th row6' 7.25''
5th row6' 4''
ValueCountFrequency (%)
6 1046
45.5%
7 83
 
3.6%
8.5 46
 
2.0%
5 46
 
2.0%
9.5 34
 
1.5%
7.5 34
 
1.5%
8.75 33
 
1.4%
6.75 32
 
1.4%
5.75 31
 
1.3%
7.75 30
 
1.3%
Other values (109) 885
38.5%
2023-07-13T22:07:25.169619image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 3615
36.9%
6 1249
 
12.7%
1095
 
11.2%
5 1037
 
10.6%
. 943
 
9.6%
7 489
 
5.0%
2 334
 
3.4%
1 314
 
3.2%
0 286
 
2.9%
8 143
 
1.5%
Other values (3) 302
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 4558
46.5%
Decimal Number 4154
42.4%
Space Separator 1095
 
11.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1249
30.1%
5 1037
25.0%
7 489
 
11.8%
2 334
 
8.0%
1 314
 
7.6%
0 286
 
6.9%
8 143
 
3.4%
9 129
 
3.1%
4 101
 
2.4%
3 72
 
1.7%
Other Punctuation
ValueCountFrequency (%)
' 3615
79.3%
. 943
 
20.7%
Space Separator
ValueCountFrequency (%)
1095
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 9807
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
' 3615
36.9%
6 1249
 
12.7%
1095
 
11.2%
5 1037
 
10.6%
. 943
 
9.6%
7 489
 
5.0%
2 334
 
3.4%
1 314
 
3.2%
0 286
 
2.9%
8 143
 
1.5%
Other values (3) 302
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9807
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 3615
36.9%
6 1249
 
12.7%
1095
 
11.2%
5 1037
 
10.6%
. 943
 
9.6%
7 489
 
5.0%
2 334
 
3.4%
1 314
 
3.2%
0 286
 
2.9%
8 143
 
1.5%
Other values (3) 302
 
3.1%

weight
Text

MISSING 

Distinct630
Distinct (%)40.0%
Missing59
Missing (%)3.6%
Memory size12.9 KiB
2023-07-13T22:07:25.473908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.193138501
Min length0

Characters and Unicode

Total characters6600
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique332 ?
Unique (%)21.1%

Sample

1st row271
2nd row219
3rd row235.5
4th row287
5th row243
ValueCountFrequency (%)
198 15
 
1.0%
214 14
 
0.9%
200 14
 
0.9%
223 14
 
0.9%
218 13
 
0.8%
208 13
 
0.8%
227 13
 
0.8%
212 12
 
0.8%
215 12
 
0.8%
228 12
 
0.8%
Other values (619) 1441
91.6%
2023-07-13T22:07:25.834826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1651
25.0%
1 860
13.0%
. 844
12.8%
0 625
 
9.5%
8 519
 
7.9%
4 477
 
7.2%
6 425
 
6.4%
9 359
 
5.4%
3 327
 
5.0%
5 258
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5756
87.2%
Other Punctuation 844
 
12.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1651
28.7%
1 860
14.9%
0 625
 
10.9%
8 519
 
9.0%
4 477
 
8.3%
6 425
 
7.4%
9 359
 
6.2%
3 327
 
5.7%
5 258
 
4.5%
7 255
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 844
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1651
25.0%
1 860
13.0%
. 844
12.8%
0 625
 
9.5%
8 519
 
7.9%
4 477
 
7.2%
6 425
 
6.4%
9 359
 
5.4%
3 327
 
5.0%
5 258
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1651
25.0%
1 860
13.0%
. 844
12.8%
0 625
 
9.5%
8 519
 
7.9%
4 477
 
7.2%
6 425
 
6.4%
9 359
 
5.4%
3 327
 
5.0%
5 258
 
3.9%

wingspan
Real number (ℝ)

MISSING 

Distinct91
Distinct (%)5.8%
Missing58
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean82.40228571
Minimum70
Maximum98.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:25.909743image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile75.25
Q179.75
median82.5
Q385.25
95-th percentile88.5
Maximum98.25
Range28.25
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation4.006972304
Coefficient of variation (CV)0.04862695579
Kurtosis-0.05451714106
Mean82.40228571
Median Absolute Deviation (MAD)2.75
Skewness-0.2245036642
Sum129783.6
Variance16.05582705
MonotonicityNot monotonic
2023-07-13T22:07:25.966597image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
82 60
 
3.7%
84 59
 
3.6%
83 51
 
3.1%
81 51
 
3.1%
83.5 47
 
2.9%
85 45
 
2.8%
86 43
 
2.6%
81.5 43
 
2.6%
80 42
 
2.6%
84.5 42
 
2.6%
Other values (81) 1092
66.9%
(Missing) 58
 
3.6%
ValueCountFrequency (%)
70 2
0.1%
70.75 2
0.1%
71.5 3
0.2%
71.75 2
0.1%
72 3
0.2%
ValueCountFrequency (%)
98.25 1
0.1%
94.5 1
0.1%
94 1
0.1%
92.75 1
0.1%
92.5 2
0.1%

wingspan_ft_in
Text

MISSING 

Distinct166
Distinct (%)10.5%
Missing58
Missing (%)3.6%
Memory size12.9 KiB
2023-07-13T22:07:26.138036image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.933333333
Min length6

Characters and Unicode

Total characters12495
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)2.5%

Sample

1st row7' 2.5''
2nd row6' 8.5''
3rd row7' 3.5''
4th row7' 0''
5th row7' 2''
ValueCountFrequency (%)
6 920
30.3%
7 598
19.7%
10 57
 
1.9%
0 55
 
1.8%
1 47
 
1.5%
9 46
 
1.5%
11.5 45
 
1.5%
3 43
 
1.4%
2 43
 
1.4%
11 42
 
1.4%
Other values (112) 1144
37.6%
2023-07-13T22:07:26.395121image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 4725
37.8%
1465
 
11.7%
5 1104
 
8.8%
. 1082
 
8.7%
6 1062
 
8.5%
7 968
 
7.7%
1 607
 
4.9%
0 496
 
4.0%
2 479
 
3.8%
9 156
 
1.2%
Other values (3) 351
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 5807
46.5%
Decimal Number 5223
41.8%
Space Separator 1465
 
11.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1104
21.1%
6 1062
20.3%
7 968
18.5%
1 607
11.6%
0 496
9.5%
2 479
9.2%
9 156
 
3.0%
3 127
 
2.4%
8 120
 
2.3%
4 104
 
2.0%
Other Punctuation
ValueCountFrequency (%)
' 4725
81.4%
. 1082
 
18.6%
Space Separator
ValueCountFrequency (%)
1465
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12495
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
' 4725
37.8%
1465
 
11.7%
5 1104
 
8.8%
. 1082
 
8.7%
6 1062
 
8.5%
7 968
 
7.7%
1 607
 
4.9%
0 496
 
4.0%
2 479
 
3.8%
9 156
 
1.2%
Other values (3) 351
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 4725
37.8%
1465
 
11.7%
5 1104
 
8.8%
. 1082
 
8.7%
6 1062
 
8.5%
7 968
 
7.7%
1 607
 
4.9%
0 496
 
4.0%
2 479
 
3.8%
9 156
 
1.2%
Other values (3) 351
 
2.8%

standing_reach
Real number (ℝ)

MISSING 

Distinct62
Distinct (%)3.9%
Missing59
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean103.5089898
Minimum88.5
Maximum122.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:26.479997image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum88.5
5-th percentile95
Q1100
median104
Q3107
95-th percentile111
Maximum122.5
Range34
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.878399937
Coefficient of variation (CV)0.04713020526
Kurtosis-0.2892763642
Mean103.5089898
Median Absolute Deviation (MAD)3.5
Skewness-0.2200175068
Sum162923.15
Variance23.79878595
MonotonicityNot monotonic
2023-07-13T22:07:26.550294image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
103.5 68
 
4.2%
106.5 67
 
4.1%
107 64
 
3.9%
104 61
 
3.7%
103 60
 
3.7%
105.5 60
 
3.7%
102 58
 
3.6%
107.5 58
 
3.6%
106 57
 
3.5%
104.5 56
 
3.4%
Other values (52) 965
59.1%
(Missing) 59
 
3.6%
ValueCountFrequency (%)
88.5 2
0.1%
89.5 1
0.1%
90 1
0.1%
90.5 1
0.1%
91 1
0.1%
ValueCountFrequency (%)
122.5 1
 
0.1%
117 1
 
0.1%
116 1
 
0.1%
115.5 3
0.2%
115 1
 
0.1%

standing_reach_ft_in
Text

MISSING 

Distinct153
Distinct (%)9.7%
Missing59
Missing (%)3.6%
Memory size12.9 KiB
2023-07-13T22:07:26.729349image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.370393901
Min length6

Characters and Unicode

Total characters11601
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)3.1%

Sample

1st row9' 1''
2nd row8' 7''
3rd row9' 0''
4th row8' 7''
5th row9' 2''
ValueCountFrequency (%)
8 1120
36.9%
9 354
 
11.7%
7 151
 
5.0%
10.5 73
 
2.4%
11 71
 
2.3%
0 68
 
2.2%
1.5 67
 
2.2%
2 66
 
2.2%
11.5 64
 
2.1%
1 64
 
2.1%
Other values (99) 940
30.9%
2023-07-13T22:07:26.967208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 4722
40.7%
1464
 
12.6%
8 1289
 
11.1%
. 891
 
7.7%
5 885
 
7.6%
1 605
 
5.2%
0 593
 
5.1%
9 444
 
3.8%
7 240
 
2.1%
2 137
 
1.2%
Other values (3) 331
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Other Punctuation 5613
48.4%
Decimal Number 4524
39.0%
Space Separator 1464
 
12.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1289
28.5%
5 885
19.6%
1 605
13.4%
0 593
13.1%
9 444
 
9.8%
7 240
 
5.3%
2 137
 
3.0%
3 114
 
2.5%
6 109
 
2.4%
4 108
 
2.4%
Other Punctuation
ValueCountFrequency (%)
' 4722
84.1%
. 891
 
15.9%
Space Separator
ValueCountFrequency (%)
1464
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11601
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
' 4722
40.7%
1464
 
12.6%
8 1289
 
11.1%
. 891
 
7.7%
5 885
 
7.6%
1 605
 
5.2%
0 593
 
5.1%
9 444
 
3.8%
7 240
 
2.1%
2 137
 
1.2%
Other values (3) 331
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11601
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
' 4722
40.7%
1464
 
12.6%
8 1289
 
11.1%
. 891
 
7.7%
5 885
 
7.6%
1 605
 
5.2%
0 593
 
5.1%
9 444
 
3.8%
7 240
 
2.1%
2 137
 
1.2%
Other values (3) 331
 
2.9%

body_fat_pct
Text

MISSING 

Distinct201
Distinct (%)15.8%
Missing357
Missing (%)21.9%
Memory size12.9 KiB
2023-07-13T22:07:27.218014image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.274294671
Min length3

Characters and Unicode

Total characters4178
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)4.8%

Sample

1st row12.4
2nd row5.3
3rd row9.3
4th row9.3
5th row5.3
ValueCountFrequency (%)
6.7 59
 
4.6%
8.0 45
 
3.5%
5.3 33
 
2.6%
6.0 30
 
2.4%
5.0 26
 
2.0%
5.4 24
 
1.9%
9.3 24
 
1.9%
5.6 24
 
1.9%
5.9 23
 
1.8%
6.2 22
 
1.7%
Other values (191) 966
75.7%
2023-07-13T22:07:27.512729image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1276
30.5%
5 512
12.3%
6 372
 
8.9%
1 359
 
8.6%
7 304
 
7.3%
4 269
 
6.4%
8 259
 
6.2%
0 248
 
5.9%
9 207
 
5.0%
3 204
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2902
69.5%
Other Punctuation 1276
30.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 512
17.6%
6 372
12.8%
1 359
12.4%
7 304
10.5%
4 269
9.3%
8 259
8.9%
0 248
8.5%
9 207
7.1%
3 204
 
7.0%
2 168
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 1276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4178
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1276
30.5%
5 512
12.3%
6 372
 
8.9%
1 359
 
8.6%
7 304
 
7.3%
4 269
 
6.4%
8 259
 
6.2%
0 248
 
5.9%
9 207
 
5.0%
3 204
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4178
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1276
30.5%
5 512
12.3%
6 372
 
8.9%
1 359
 
8.6%
7 304
 
7.3%
4 269
 
6.4%
8 259
 
6.2%
0 248
 
5.9%
9 207
 
5.0%
3 204
 
4.9%

hand_length
Text

MISSING 

Distinct13
Distinct (%)1.5%
Missing794
Missing (%)48.6%
Memory size12.9 KiB
2023-07-13T22:07:27.622075image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.438617402
Min length3

Characters and Unicode

Total characters2885
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row9.25
2nd row9.0
3rd row9.5
4th row8.5
5th row8.5
ValueCountFrequency (%)
8.5 188
22.4%
9.0 171
20.4%
8.75 138
16.4%
8.25 109
13.0%
9.25 84
10.0%
8.0 62
 
7.4%
9.5 42
 
5.0%
9.75 17
 
2.0%
7.75 11
 
1.3%
7.5 10
 
1.2%
Other values (3) 7
 
0.8%
2023-07-13T22:07:27.775405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 839
29.1%
5 602
20.9%
8 497
17.2%
9 314
 
10.9%
0 244
 
8.5%
2 195
 
6.8%
7 187
 
6.5%
1 7
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2046
70.9%
Other Punctuation 839
29.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 602
29.4%
8 497
24.3%
9 314
15.3%
0 244
11.9%
2 195
 
9.5%
7 187
 
9.1%
1 7
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 839
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2885
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 839
29.1%
5 602
20.9%
8 497
17.2%
9 314
 
10.9%
0 244
 
8.5%
2 195
 
6.8%
7 187
 
6.5%
1 7
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2885
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 839
29.1%
5 602
20.9%
8 497
17.2%
9 314
 
10.9%
0 244
 
8.5%
2 195
 
6.8%
7 187
 
6.5%
1 7
 
0.2%

hand_width
Text

MISSING 

Distinct21
Distinct (%)2.5%
Missing794
Missing (%)48.6%
Memory size12.9 KiB
2023-07-13T22:07:27.886460image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.672228844
Min length3

Characters and Unicode

Total characters3081
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.5%

Sample

1st row9.25
2nd row9.25
3rd row9.5
4th row7.25
5th row10.0
ValueCountFrequency (%)
9.5 149
17.8%
9.0 122
14.5%
9.25 97
11.6%
10.0 90
10.7%
9.75 74
8.8%
8.75 64
7.6%
8.5 64
7.6%
10.25 53
 
6.3%
10.5 40
 
4.8%
8.25 28
 
3.3%
Other values (11) 58
 
6.9%
2023-07-13T22:07:28.054190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 839
27.2%
5 602
19.5%
9 442
14.3%
0 437
14.2%
1 239
 
7.8%
2 182
 
5.9%
7 175
 
5.7%
8 165
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2242
72.8%
Other Punctuation 839
 
27.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 602
26.9%
9 442
19.7%
0 437
19.5%
1 239
 
10.7%
2 182
 
8.1%
7 175
 
7.8%
8 165
 
7.4%
Other Punctuation
ValueCountFrequency (%)
. 839
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3081
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 839
27.2%
5 602
19.5%
9 442
14.3%
0 437
14.2%
1 239
 
7.8%
2 182
 
5.9%
7 175
 
5.7%
8 165
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3081
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 839
27.2%
5 602
19.5%
9 442
14.3%
0 437
14.2%
1 239
 
7.8%
2 182
 
5.9%
7 175
 
5.7%
8 165
 
5.4%

standing_vertical_leap
Real number (ℝ)

MISSING 

Distinct41
Distinct (%)2.9%
Missing237
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean29.25483524
Minimum19.5
Maximum41.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:28.122150image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum19.5
5-th percentile24
Q127
median29
Q331.5
95-th percentile34.5
Maximum41.5
Range22
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation3.099532265
Coefficient of variation (CV)0.1059494008
Kurtosis0.04830427758
Mean29.25483524
Median Absolute Deviation (MAD)2
Skewness0.1227693058
Sum40839.75
Variance9.60710026
MonotonicityNot monotonic
2023-07-13T22:07:28.177321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
28.5 108
 
6.6%
29 89
 
5.5%
29.5 88
 
5.4%
30.5 87
 
5.3%
27.5 77
 
4.7%
31.5 77
 
4.7%
28 74
 
4.5%
26 72
 
4.4%
30 72
 
4.4%
27 71
 
4.3%
Other values (31) 581
35.6%
(Missing) 237
14.5%
ValueCountFrequency (%)
19.5 1
 
0.1%
20.5 1
 
0.1%
21 3
0.2%
21.5 4
0.2%
22 3
0.2%
ValueCountFrequency (%)
41.5 1
 
0.1%
39.5 2
 
0.1%
38.5 1
 
0.1%
38 2
 
0.1%
37.5 6
0.4%

max_vertical_leap
Real number (ℝ)

MISSING 

Distinct44
Distinct (%)3.2%
Missing237
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean34.52148997
Minimum21
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:28.232637image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum21
5-th percentile28.5
Q132
median34.5
Q337
95-th percentile40.625
Maximum48
Range27
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.704144274
Coefficient of variation (CV)0.107299664
Kurtosis-0.05742427604
Mean34.52148997
Median Absolute Deviation (MAD)2.5
Skewness0.05460691295
Sum48192
Variance13.7206848
MonotonicityNot monotonic
2023-07-13T22:07:28.293406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
33 83
 
5.1%
35 82
 
5.0%
35.5 82
 
5.0%
36.5 71
 
4.3%
34 68
 
4.2%
34.5 67
 
4.1%
32.5 65
 
4.0%
37.5 64
 
3.9%
33.5 63
 
3.9%
31.5 58
 
3.6%
Other values (34) 693
42.4%
(Missing) 237
 
14.5%
ValueCountFrequency (%)
21 1
 
0.1%
22.5 1
 
0.1%
25 4
0.2%
25.5 2
 
0.1%
26 8
0.5%
ValueCountFrequency (%)
48 1
 
0.1%
45.5 1
 
0.1%
44.5 2
 
0.1%
44 4
0.2%
43.5 5
0.3%

lane_agility_time
Real number (ℝ)

MISSING 

Distinct272
Distinct (%)19.6%
Missing246
Missing (%)15.1%
Infinite0
Infinite (%)0.0%
Mean11.41385725
Minimum9.65
Maximum14.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:28.353709image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum9.65
5-th percentile10.57
Q110.99
median11.35
Q311.75
95-th percentile12.52
Maximum14.45
Range4.8
Interquartile range (IQR)0.76

Descriptive statistics

Standard deviation0.598113354
Coefficient of variation (CV)0.05240238607
Kurtosis1.101734533
Mean11.41385725
Median Absolute Deviation (MAD)0.37
Skewness0.7588870612
Sum15831.02
Variance0.3577395842
MonotonicityNot monotonic
2023-07-13T22:07:28.413559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11.21 16
 
1.0%
11.3 15
 
0.9%
11.26 15
 
0.9%
11 15
 
0.9%
11.2 14
 
0.9%
11.12 14
 
0.9%
11.65 14
 
0.9%
11.15 14
 
0.9%
11.51 13
 
0.8%
11.48 13
 
0.8%
Other values (262) 1244
76.2%
(Missing) 246
 
15.1%
ValueCountFrequency (%)
9.65 1
0.1%
9.97 1
0.1%
9.99 1
0.1%
10.07 1
0.1%
10.08 1
0.1%
ValueCountFrequency (%)
14.45 1
0.1%
14.01 1
0.1%
13.8 1
0.1%
13.7 1
0.1%
13.44 1
0.1%

modified_lane_agility_time
Real number (ℝ)

MISSING 

Distinct109
Distinct (%)21.4%
Missing1124
Missing (%)68.8%
Infinite0
Infinite (%)0.0%
Mean3.088172888
Minimum2.22
Maximum3.76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:28.471818image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.22
5-th percentile2.664
Q12.98
median3.1
Q33.23
95-th percentile3.41
Maximum3.76
Range1.54
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.2200152142
Coefficient of variation (CV)0.07124446141
Kurtosis1.482667635
Mean3.088172888
Median Absolute Deviation (MAD)0.12
Skewness-0.6470814006
Sum1571.88
Variance0.04840669446
MonotonicityNot monotonic
2023-07-13T22:07:28.530832image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.1 16
 
1.0%
3.08 14
 
0.9%
3.03 14
 
0.9%
3.12 14
 
0.9%
3.19 13
 
0.8%
3.05 13
 
0.8%
3.2 13
 
0.8%
3.04 13
 
0.8%
3.02 12
 
0.7%
3.15 12
 
0.7%
Other values (99) 375
 
23.0%
(Missing) 1124
68.8%
ValueCountFrequency (%)
2.22 1
0.1%
2.28 1
0.1%
2.4 1
0.1%
2.42 1
0.1%
2.43 1
0.1%
ValueCountFrequency (%)
3.76 1
0.1%
3.7 1
0.1%
3.65 1
0.1%
3.61 2
0.1%
3.54 2
0.1%

three_quarter_sprint
Real number (ℝ)

MISSING 

Distinct80
Distinct (%)5.8%
Missing246
Missing (%)15.1%
Infinite0
Infinite (%)0.0%
Mean3.280497477
Minimum2.91
Maximum3.81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:28.596224image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.91
5-th percentile3.08
Q13.19
median3.27
Q33.36
95-th percentile3.52
Maximum3.81
Range0.9
Interquartile range (IQR)0.17

Descriptive statistics

Standard deviation0.1339179735
Coefficient of variation (CV)0.04082245892
Kurtosis0.4804511201
Mean3.280497477
Median Absolute Deviation (MAD)0.08
Skewness0.553267592
Sum4550.05
Variance0.01793402362
MonotonicityNot monotonic
2023-07-13T22:07:28.656419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.2 62
 
3.8%
3.25 62
 
3.8%
3.27 58
 
3.6%
3.22 45
 
2.8%
3.21 43
 
2.6%
3.28 41
 
2.5%
3.3 41
 
2.5%
3.29 41
 
2.5%
3.19 40
 
2.4%
3.26 39
 
2.4%
Other values (70) 915
56.0%
(Missing) 246
 
15.1%
ValueCountFrequency (%)
2.91 1
0.1%
2.92 1
0.1%
2.96 2
0.1%
2.98 2
0.1%
2.99 1
0.1%
ValueCountFrequency (%)
3.81 1
0.1%
3.8 1
0.1%
3.78 1
0.1%
3.73 1
0.1%
3.72 1
0.1%

bench_press
Real number (ℝ)

MISSING  ZEROS 

Distinct28
Distinct (%)2.6%
Missing538
Missing (%)32.9%
Infinite0
Infinite (%)0.0%
Mean10.31415525
Minimum0
Maximum27
Zeros40
Zeros (%)2.4%
Negative0
Negative (%)0.0%
Memory size12.9 KiB
2023-07-13T22:07:28.709109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median10
Q314
95-th percentile19
Maximum27
Range27
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.541428695
Coefficient of variation (CV)0.5372644255
Kurtosis-0.3206440317
Mean10.31415525
Median Absolute Deviation (MAD)4
Skewness0.1495596074
Sum11294
Variance30.70743199
MonotonicityNot monotonic
2023-07-13T22:07:28.760598image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
13 84
 
5.1%
10 83
 
5.1%
15 79
 
4.8%
8 72
 
4.4%
12 70
 
4.3%
9 69
 
4.2%
11 66
 
4.0%
7 62
 
3.8%
14 58
 
3.6%
6 52
 
3.2%
Other values (18) 400
24.5%
(Missing) 538
32.9%
ValueCountFrequency (%)
0 40
2.4%
1 32
2.0%
2 41
2.5%
3 29
1.8%
4 34
2.1%
ValueCountFrequency (%)
27 1
 
0.1%
26 4
0.2%
25 5
0.3%
24 6
0.4%
23 2
 
0.1%
Distinct8
Distinct (%)7.7%
Missing1529
Missing (%)93.6%
Memory size12.9 KiB
2023-07-13T22:07:28.842878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters312
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st row4-5
2nd row2-5
3rd row3-5
4th row3-5
5th row1-5
ValueCountFrequency (%)
3-5 31
29.8%
4-5 27
26.0%
2-5 20
19.2%
1-5 12
 
11.5%
5-5 10
 
9.6%
0-5 2
 
1.9%
3-4 1
 
1.0%
2-3 1
 
1.0%
2023-07-13T22:07:28.994252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 112
35.9%
- 104
33.3%
3 33
 
10.6%
4 28
 
9.0%
2 21
 
6.7%
1 12
 
3.8%
0 2
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 208
66.7%
Dash Punctuation 104
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 112
53.8%
3 33
 
15.9%
4 28
 
13.5%
2 21
 
10.1%
1 12
 
5.8%
0 2
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 112
35.9%
- 104
33.3%
3 33
 
10.6%
4 28
 
9.0%
2 21
 
6.7%
1 12
 
3.8%
0 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 112
35.9%
- 104
33.3%
3 33
 
10.6%
4 28
 
9.0%
2 21
 
6.7%
1 12
 
3.8%
0 2
 
0.6%
Distinct5
Distinct (%)4.7%
Missing1527
Missing (%)93.5%
Memory size12.9 KiB
2023-07-13T22:07:29.079991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters318
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3-5
2nd row3-5
3rd row2-5
4th row3-5
5th row2-5
ValueCountFrequency (%)
3-5 41
38.7%
4-5 23
21.7%
2-5 19
17.9%
5-5 18
17.0%
1-5 5
 
4.7%
2023-07-13T22:07:29.216898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 124
39.0%
- 106
33.3%
3 41
 
12.9%
4 23
 
7.2%
2 19
 
6.0%
1 5
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 212
66.7%
Dash Punctuation 106
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 124
58.5%
3 41
 
19.3%
4 23
 
10.8%
2 19
 
9.0%
1 5
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 318
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 124
39.0%
- 106
33.3%
3 41
 
12.9%
4 23
 
7.2%
2 19
 
6.0%
1 5
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 124
39.0%
- 106
33.3%
3 41
 
12.9%
4 23
 
7.2%
2 19
 
6.0%
1 5
 
1.6%

spot_fifteen_top_key
Text

MISSING 

Distinct5
Distinct (%)4.7%
Missing1527
Missing (%)93.5%
Memory size12.9 KiB
2023-07-13T22:07:29.494564image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters318
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4-5
2nd row5-5
3rd row4-5
4th row4-5
5th row2-5
ValueCountFrequency (%)
3-5 33
31.1%
4-5 31
29.2%
5-5 18
17.0%
2-5 18
17.0%
1-5 6
 
5.7%
2023-07-13T22:07:29.660711image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 124
39.0%
- 106
33.3%
3 33
 
10.4%
4 31
 
9.7%
2 18
 
5.7%
1 6
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 212
66.7%
Dash Punctuation 106
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 124
58.5%
3 33
 
15.6%
4 31
 
14.6%
2 18
 
8.5%
1 6
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 318
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 124
39.0%
- 106
33.3%
3 33
 
10.4%
4 31
 
9.7%
2 18
 
5.7%
1 6
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 124
39.0%
- 106
33.3%
3 33
 
10.4%
4 31
 
9.7%
2 18
 
5.7%
1 6
 
1.9%
Distinct6
Distinct (%)5.7%
Missing1527
Missing (%)93.5%
Memory size12.9 KiB
2023-07-13T22:07:29.741025image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters318
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4-5
2nd row4-5
3rd row5-5
4th row3-5
5th row5-5
ValueCountFrequency (%)
4-5 38
35.8%
3-5 25
23.6%
2-5 17
16.0%
5-5 13
 
12.3%
1-5 11
 
10.4%
0-5 2
 
1.9%
2023-07-13T22:07:29.867005image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 119
37.4%
- 106
33.3%
4 38
 
11.9%
3 25
 
7.9%
2 17
 
5.3%
1 11
 
3.5%
0 2
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 212
66.7%
Dash Punctuation 106
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 119
56.1%
4 38
 
17.9%
3 25
 
11.8%
2 17
 
8.0%
1 11
 
5.2%
0 2
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 318
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 119
37.4%
- 106
33.3%
4 38
 
11.9%
3 25
 
7.9%
2 17
 
5.3%
1 11
 
3.5%
0 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 119
37.4%
- 106
33.3%
4 38
 
11.9%
3 25
 
7.9%
2 17
 
5.3%
1 11
 
3.5%
0 2
 
0.6%
Distinct6
Distinct (%)5.7%
Missing1527
Missing (%)93.5%
Memory size12.9 KiB
2023-07-13T22:07:29.954015image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters318
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st row3-5
2nd row3-5
3rd row4-5
4th row4-5
5th row3-5
ValueCountFrequency (%)
3-5 37
34.9%
4-5 33
31.1%
2-5 19
17.9%
5-5 13
 
12.3%
1-5 3
 
2.8%
2-4 1
 
0.9%
2023-07-13T22:07:30.085905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 118
37.1%
- 106
33.3%
3 37
 
11.6%
4 34
 
10.7%
2 20
 
6.3%
1 3
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 212
66.7%
Dash Punctuation 106
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 118
55.7%
3 37
 
17.5%
4 34
 
16.0%
2 20
 
9.4%
1 3
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 318
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 118
37.1%
- 106
33.3%
3 37
 
11.6%
4 34
 
10.7%
2 20
 
6.3%
1 3
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 118
37.1%
- 106
33.3%
3 37
 
11.6%
4 34
 
10.7%
2 20
 
6.3%
1 3
 
0.9%
Distinct25
Distinct (%)8.6%
Missing1341
Missing (%)82.1%
Memory size12.9 KiB
2023-07-13T22:07:30.393306image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.770547945
Min length3

Characters and Unicode

Total characters1101
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)1.4%

Sample

1st row2-5
2nd row3-5
3rd row2-5
4th row2-5
5th row3-5
ValueCountFrequency (%)
3-5 53
18.2%
4-5 40
13.7%
2-5 31
10.6%
5-5 22
 
7.5%
15-25 20
 
6.8%
1-5 20
 
6.8%
16-25 16
 
5.5%
17-25 11
 
3.8%
12-25 10
 
3.4%
14-25 10
 
3.4%
Other values (15) 59
20.2%
2023-07-13T22:07:30.560210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 332
30.2%
- 292
26.5%
2 169
15.3%
1 129
 
11.7%
3 59
 
5.4%
4 52
 
4.7%
6 17
 
1.5%
9 17
 
1.5%
7 14
 
1.3%
0 12
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 809
73.5%
Dash Punctuation 292
 
26.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 332
41.0%
2 169
20.9%
1 129
 
15.9%
3 59
 
7.3%
4 52
 
6.4%
6 17
 
2.1%
9 17
 
2.1%
7 14
 
1.7%
0 12
 
1.5%
8 8
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 292
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1101
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 332
30.2%
- 292
26.5%
2 169
15.3%
1 129
 
11.7%
3 59
 
5.4%
4 52
 
4.7%
6 17
 
1.5%
9 17
 
1.5%
7 14
 
1.3%
0 12
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1101
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 332
30.2%
- 292
26.5%
2 169
15.3%
1 129
 
11.7%
3 59
 
5.4%
4 52
 
4.7%
6 17
 
1.5%
9 17
 
1.5%
7 14
 
1.3%
0 12
 
1.1%
Distinct8
Distinct (%)4.7%
Missing1462
Missing (%)89.5%
Memory size12.9 KiB
2023-07-13T22:07:30.652444image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters513
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row3-5
2nd row1-5
3rd row5-5
4th row3-5
5th row2-5
ValueCountFrequency (%)
3-5 49
28.7%
4-5 43
25.1%
2-5 31
18.1%
5-5 23
13.5%
1-5 19
 
11.1%
0-5 3
 
1.8%
5-6 2
 
1.2%
3-6 1
 
0.6%
2023-07-13T22:07:30.788967image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 193
37.6%
- 171
33.3%
3 50
 
9.7%
4 43
 
8.4%
2 31
 
6.0%
1 19
 
3.7%
0 3
 
0.6%
6 3
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 342
66.7%
Dash Punctuation 171
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 193
56.4%
3 50
 
14.6%
4 43
 
12.6%
2 31
 
9.1%
1 19
 
5.6%
0 3
 
0.9%
6 3
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 513
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 193
37.6%
- 171
33.3%
3 50
 
9.7%
4 43
 
8.4%
2 31
 
6.0%
1 19
 
3.7%
0 3
 
0.6%
6 3
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 193
37.6%
- 171
33.3%
3 50
 
9.7%
4 43
 
8.4%
2 31
 
6.0%
1 19
 
3.7%
0 3
 
0.6%
6 3
 
0.6%

spot_college_top_key
Text

MISSING 

Distinct8
Distinct (%)4.7%
Missing1462
Missing (%)89.5%
Memory size12.9 KiB
2023-07-13T22:07:30.875740image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters513
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.2%

Sample

1st row3-5
2nd row3-5
3rd row3-5
4th row2-5
5th row2-5
ValueCountFrequency (%)
3-5 54
31.6%
4-5 44
25.7%
2-5 31
18.1%
5-5 24
14.0%
1-5 14
 
8.2%
0-5 2
 
1.2%
3-4 1
 
0.6%
4-6 1
 
0.6%
2023-07-13T22:07:31.010049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 193
37.6%
- 171
33.3%
3 55
 
10.7%
4 46
 
9.0%
2 31
 
6.0%
1 14
 
2.7%
0 2
 
0.4%
6 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 342
66.7%
Dash Punctuation 171
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 193
56.4%
3 55
 
16.1%
4 46
 
13.5%
2 31
 
9.1%
1 14
 
4.1%
0 2
 
0.6%
6 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 513
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 193
37.6%
- 171
33.3%
3 55
 
10.7%
4 46
 
9.0%
2 31
 
6.0%
1 14
 
2.7%
0 2
 
0.4%
6 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 193
37.6%
- 171
33.3%
3 55
 
10.7%
4 46
 
9.0%
2 31
 
6.0%
1 14
 
2.7%
0 2
 
0.4%
6 1
 
0.2%
Distinct6
Distinct (%)3.5%
Missing1462
Missing (%)89.5%
Memory size12.9 KiB
2023-07-13T22:07:31.096949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters513
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row4-5
2nd row4-5
3rd row5-5
4th row3-5
5th row4-5
ValueCountFrequency (%)
3-5 57
33.3%
4-5 48
28.1%
2-5 28
16.4%
5-5 19
 
11.1%
1-5 18
 
10.5%
4-6 1
 
0.6%
2023-07-13T22:07:31.230396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 189
36.8%
- 171
33.3%
3 57
 
11.1%
4 49
 
9.6%
2 28
 
5.5%
1 18
 
3.5%
6 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 342
66.7%
Dash Punctuation 171
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 189
55.3%
3 57
 
16.7%
4 49
 
14.3%
2 28
 
8.2%
1 18
 
5.3%
6 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 513
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 189
36.8%
- 171
33.3%
3 57
 
11.1%
4 49
 
9.6%
2 28
 
5.5%
1 18
 
3.5%
6 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 189
36.8%
- 171
33.3%
3 57
 
11.1%
4 49
 
9.6%
2 28
 
5.5%
1 18
 
3.5%
6 1
 
0.2%
Distinct6
Distinct (%)3.5%
Missing1462
Missing (%)89.5%
Memory size12.9 KiB
2023-07-13T22:07:31.319074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters513
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4-5
2nd row4-5
3rd row4-5
4th row3-5
5th row4-5
ValueCountFrequency (%)
3-5 55
32.2%
4-5 43
25.1%
2-5 40
23.4%
1-5 15
 
8.8%
5-5 14
 
8.2%
0-5 4
 
2.3%
2023-07-13T22:07:31.452982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 185
36.1%
- 171
33.3%
3 55
 
10.7%
4 43
 
8.4%
2 40
 
7.8%
1 15
 
2.9%
0 4
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 342
66.7%
Dash Punctuation 171
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 185
54.1%
3 55
 
16.1%
4 43
 
12.6%
2 40
 
11.7%
1 15
 
4.4%
0 4
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 171
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 513
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 185
36.1%
- 171
33.3%
3 55
 
10.7%
4 43
 
8.4%
2 40
 
7.8%
1 15
 
2.9%
0 4
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 185
36.1%
- 171
33.3%
3 55
 
10.7%
4 43
 
8.4%
2 40
 
7.8%
1 15
 
2.9%
0 4
 
0.8%

spot_nba_corner_left
Text

MISSING 

Distinct9
Distinct (%)3.6%
Missing1381
Missing (%)84.6%
Memory size12.9 KiB
2023-07-13T22:07:31.545952image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters756
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)1.2%

Sample

1st row2-5
2nd row2-5
3rd row3-5
4th row2-5
5th row1-5
ValueCountFrequency (%)
3-5 73
29.0%
4-5 63
25.0%
2-5 62
24.6%
1-5 23
 
9.1%
5-5 21
 
8.3%
0-5 7
 
2.8%
4-4 1
 
0.4%
2-4 1
 
0.4%
3-4 1
 
0.4%
2023-07-13T22:07:31.682581image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 270
35.7%
- 252
33.3%
3 74
 
9.8%
4 67
 
8.9%
2 63
 
8.3%
1 23
 
3.0%
0 7
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 504
66.7%
Dash Punctuation 252
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 270
53.6%
3 74
 
14.7%
4 67
 
13.3%
2 63
 
12.5%
1 23
 
4.6%
0 7
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 756
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 270
35.7%
- 252
33.3%
3 74
 
9.8%
4 67
 
8.9%
2 63
 
8.3%
1 23
 
3.0%
0 7
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 270
35.7%
- 252
33.3%
3 74
 
9.8%
4 67
 
8.9%
2 63
 
8.3%
1 23
 
3.0%
0 7
 
0.9%

spot_nba_break_left
Text

MISSING 

Distinct8
Distinct (%)3.2%
Missing1381
Missing (%)84.6%
Memory size12.9 KiB
2023-07-13T22:07:31.774127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters756
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.8%

Sample

1st row2-5
2nd row4-5
3rd row1-5
4th row5-5
5th row3-5
ValueCountFrequency (%)
3-5 71
28.2%
4-5 66
26.2%
2-5 55
21.8%
1-5 29
11.5%
5-5 17
 
6.7%
0-5 12
 
4.8%
4-6 1
 
0.4%
5-6 1
 
0.4%
2023-07-13T22:07:31.914198image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 268
35.4%
- 252
33.3%
3 71
 
9.4%
4 67
 
8.9%
2 55
 
7.3%
1 29
 
3.8%
0 12
 
1.6%
6 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 504
66.7%
Dash Punctuation 252
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 268
53.2%
3 71
 
14.1%
4 67
 
13.3%
2 55
 
10.9%
1 29
 
5.8%
0 12
 
2.4%
6 2
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 756
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 268
35.4%
- 252
33.3%
3 71
 
9.4%
4 67
 
8.9%
2 55
 
7.3%
1 29
 
3.8%
0 12
 
1.6%
6 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 268
35.4%
- 252
33.3%
3 71
 
9.4%
4 67
 
8.9%
2 55
 
7.3%
1 29
 
3.8%
0 12
 
1.6%
6 2
 
0.3%

spot_nba_top_key
Text

MISSING 

Distinct7
Distinct (%)2.8%
Missing1381
Missing (%)84.6%
Memory size12.9 KiB
2023-07-13T22:07:32.004795image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters756
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row2-5
2nd row4-5
3rd row4-5
4th row2-5
5th row4-5
ValueCountFrequency (%)
3-5 73
29.0%
2-5 69
27.4%
4-5 51
20.2%
1-5 34
13.5%
5-5 20
 
7.9%
0-5 4
 
1.6%
2-6 1
 
0.4%
2023-07-13T22:07:32.141795image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 271
35.8%
- 252
33.3%
3 73
 
9.7%
2 70
 
9.3%
4 51
 
6.7%
1 34
 
4.5%
0 4
 
0.5%
6 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 504
66.7%
Dash Punctuation 252
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 271
53.8%
3 73
 
14.5%
2 70
 
13.9%
4 51
 
10.1%
1 34
 
6.7%
0 4
 
0.8%
6 1
 
0.2%
Dash Punctuation
ValueCountFrequency (%)
- 252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 756
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 271
35.8%
- 252
33.3%
3 73
 
9.7%
2 70
 
9.3%
4 51
 
6.7%
1 34
 
4.5%
0 4
 
0.5%
6 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 271
35.8%
- 252
33.3%
3 73
 
9.7%
2 70
 
9.3%
4 51
 
6.7%
1 34
 
4.5%
0 4
 
0.5%
6 1
 
0.1%

spot_nba_break_right
Text

MISSING 

Distinct7
Distinct (%)2.8%
Missing1381
Missing (%)84.6%
Memory size12.9 KiB
2023-07-13T22:07:32.226915image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters756
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3-5
2nd row3-5
3rd row1-5
4th row4-5
5th row2-5
ValueCountFrequency (%)
3-5 86
34.1%
2-5 65
25.8%
4-5 50
19.8%
1-5 27
 
10.7%
5-5 13
 
5.2%
0-5 9
 
3.6%
3-6 2
 
0.8%
2023-07-13T22:07:32.357862image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 263
34.8%
- 252
33.3%
3 88
 
11.6%
2 65
 
8.6%
4 50
 
6.6%
1 27
 
3.6%
0 9
 
1.2%
6 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 504
66.7%
Dash Punctuation 252
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 263
52.2%
3 88
 
17.5%
2 65
 
12.9%
4 50
 
9.9%
1 27
 
5.4%
0 9
 
1.8%
6 2
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 756
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 263
34.8%
- 252
33.3%
3 88
 
11.6%
2 65
 
8.6%
4 50
 
6.6%
1 27
 
3.6%
0 9
 
1.2%
6 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 263
34.8%
- 252
33.3%
3 88
 
11.6%
2 65
 
8.6%
4 50
 
6.6%
1 27
 
3.6%
0 9
 
1.2%
6 2
 
0.3%

spot_nba_corner_right
Text

MISSING 

Distinct6
Distinct (%)2.4%
Missing1381
Missing (%)84.6%
Memory size12.9 KiB
2023-07-13T22:07:32.438989image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters756
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2-5
2nd row3-5
3rd row4-5
4th row4-5
5th row3-5
ValueCountFrequency (%)
3-5 85
33.7%
4-5 61
24.2%
2-5 58
23.0%
1-5 26
 
10.3%
5-5 13
 
5.2%
0-5 9
 
3.6%
2023-07-13T22:07:32.564138image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 265
35.1%
- 252
33.3%
3 85
 
11.2%
4 61
 
8.1%
2 58
 
7.7%
1 26
 
3.4%
0 9
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 504
66.7%
Dash Punctuation 252
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 265
52.6%
3 85
 
16.9%
4 61
 
12.1%
2 58
 
11.5%
1 26
 
5.2%
0 9
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 252
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 756
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 265
35.1%
- 252
33.3%
3 85
 
11.2%
4 61
 
8.1%
2 58
 
7.7%
1 26
 
3.4%
0 9
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 756
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 265
35.1%
- 252
33.3%
3 85
 
11.2%
4 61
 
8.1%
2 58
 
7.7%
1 26
 
3.4%
0 9
 
1.2%
Distinct22
Distinct (%)10.9%
Missing1432
Missing (%)87.7%
Memory size12.9 KiB
2023-07-13T22:07:32.670402image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters603
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)1.5%

Sample

1st row4-6
2nd row4-6
3rd row4-6
4th row5-6
5th row4-6
ValueCountFrequency (%)
3-6 29
14.4%
2-4 28
13.9%
3-4 25
12.4%
4-6 21
10.4%
5-6 19
9.5%
1-4 16
8.0%
2-6 14
7.0%
4-8 8
 
4.0%
5-8 7
 
3.5%
7-8 6
 
3.0%
Other values (12) 28
13.9%
2023-07-13T22:07:32.823966image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 201
33.3%
4 111
18.4%
6 96
15.9%
3 57
 
9.5%
2 45
 
7.5%
8 34
 
5.6%
5 27
 
4.5%
1 19
 
3.2%
7 7
 
1.2%
0 6
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 402
66.7%
Dash Punctuation 201
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 111
27.6%
6 96
23.9%
3 57
14.2%
2 45
11.2%
8 34
 
8.5%
5 27
 
6.7%
1 19
 
4.7%
7 7
 
1.7%
0 6
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 201
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 603
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 201
33.3%
4 111
18.4%
6 96
15.9%
3 57
 
9.5%
2 45
 
7.5%
8 34
 
5.6%
5 27
 
4.5%
1 19
 
3.2%
7 7
 
1.2%
0 6
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 603
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 201
33.3%
4 111
18.4%
6 96
15.9%
3 57
 
9.5%
2 45
 
7.5%
8 34
 
5.6%
5 27
 
4.5%
1 19
 
3.2%
7 7
 
1.2%
0 6
 
1.0%
Distinct18
Distinct (%)9.0%
Missing1432
Missing (%)87.7%
Memory size12.9 KiB
2023-07-13T22:07:32.929066image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters603
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row4-6
2nd row5-6
3rd row4-6
4th row2-6
5th row3-6
ValueCountFrequency (%)
3-4 31
15.4%
5-6 27
13.4%
3-6 24
11.9%
2-4 21
10.4%
4-6 20
10.0%
1-4 19
9.5%
2-6 15
7.5%
6-8 10
 
5.0%
5-8 10
 
5.0%
4-8 6
 
3.0%
Other values (8) 18
9.0%
2023-07-13T22:07:33.077195image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 201
33.3%
4 105
17.4%
6 104
17.2%
3 57
 
9.5%
5 39
 
6.5%
2 38
 
6.3%
8 33
 
5.5%
1 21
 
3.5%
7 3
 
0.5%
0 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 402
66.7%
Dash Punctuation 201
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 105
26.1%
6 104
25.9%
3 57
14.2%
5 39
 
9.7%
2 38
 
9.5%
8 33
 
8.2%
1 21
 
5.2%
7 3
 
0.7%
0 2
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 201
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 603
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 201
33.3%
4 105
17.4%
6 104
17.2%
3 57
 
9.5%
5 39
 
6.5%
2 38
 
6.3%
8 33
 
5.5%
1 21
 
3.5%
7 3
 
0.5%
0 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 603
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 201
33.3%
4 105
17.4%
6 104
17.2%
3 57
 
9.5%
5 39
 
6.5%
2 38
 
6.3%
8 33
 
5.5%
1 21
 
3.5%
7 3
 
0.5%
0 2
 
0.3%
Distinct20
Distinct (%)10.0%
Missing1432
Missing (%)87.7%
Memory size12.9 KiB
2023-07-13T22:07:33.183529image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.004975124
Min length3

Characters and Unicode

Total characters604
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)2.0%

Sample

1st row5-6
2nd row3-6
3rd row4-6
4th row6-6
5th row1-6
ValueCountFrequency (%)
4-6 28
13.9%
3-4 26
12.9%
5-6 23
11.4%
3-6 21
10.4%
1-4 20
10.0%
2-4 16
8.0%
6-8 9
 
4.5%
4-4 9
 
4.5%
4-8 8
 
4.0%
5-8 7
 
3.5%
Other values (10) 34
16.9%
2023-07-13T22:07:33.339205image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 201
33.3%
4 121
20.0%
6 106
17.5%
3 49
 
8.1%
8 34
 
5.6%
5 30
 
5.0%
1 28
 
4.6%
2 27
 
4.5%
0 6
 
1.0%
7 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 403
66.7%
Dash Punctuation 201
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 121
30.0%
6 106
26.3%
3 49
12.2%
8 34
 
8.4%
5 30
 
7.4%
1 28
 
6.9%
2 27
 
6.7%
0 6
 
1.5%
7 2
 
0.5%
Dash Punctuation
ValueCountFrequency (%)
- 201
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 604
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 201
33.3%
4 121
20.0%
6 106
17.5%
3 49
 
8.1%
8 34
 
5.6%
5 30
 
5.0%
1 28
 
4.6%
2 27
 
4.5%
0 6
 
1.0%
7 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 604
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 201
33.3%
4 121
20.0%
6 106
17.5%
3 49
 
8.1%
8 34
 
5.6%
5 30
 
5.0%
1 28
 
4.6%
2 27
 
4.5%
0 6
 
1.0%
7 2
 
0.3%
Distinct28
Distinct (%)18.7%
Missing1483
Missing (%)90.8%
Memory size12.9 KiB
2023-07-13T22:07:33.471325image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.586666667
Min length3

Characters and Unicode

Total characters688
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)4.0%

Sample

1st row4-8
2nd row5-8
3rd row5-8
4th row4-8
5th row5-8
ValueCountFrequency (%)
15-30 16
 
10.7%
19-30 14
 
9.3%
17-30 14
 
9.3%
21-30 14
 
9.3%
18-30 14
 
9.3%
22-30 8
 
5.3%
2-4 7
 
4.7%
23-30 7
 
4.7%
14-30 7
 
4.7%
3-4 6
 
4.0%
Other values (18) 43
28.7%
2023-07-13T22:07:33.660105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 150
21.8%
3 137
19.9%
0 124
18.0%
1 94
13.7%
2 62
9.0%
4 35
 
5.1%
5 23
 
3.3%
8 23
 
3.3%
7 15
 
2.2%
9 14
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 538
78.2%
Dash Punctuation 150
 
21.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 137
25.5%
0 124
23.0%
1 94
17.5%
2 62
11.5%
4 35
 
6.5%
5 23
 
4.3%
8 23
 
4.3%
7 15
 
2.8%
9 14
 
2.6%
6 11
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 688
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 150
21.8%
3 137
19.9%
0 124
18.0%
1 94
13.7%
2 62
9.0%
4 35
 
5.1%
5 23
 
3.3%
8 23
 
3.3%
7 15
 
2.2%
9 14
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 688
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 150
21.8%
3 137
19.9%
0 124
18.0%
1 94
13.7%
2 62
9.0%
4 35
 
5.1%
5 23
 
3.3%
8 23
 
3.3%
7 15
 
2.2%
9 14
 
2.0%
Distinct13
Distinct (%)41.9%
Missing1602
Missing (%)98.1%
Memory size12.9 KiB
2023-07-13T22:07:33.753518image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters93
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)19.4%

Sample

1st row6-8
2nd row3-8
3rd row3-8
4th row5-8
5th row1-8
ValueCountFrequency (%)
3-4 8
25.8%
2-4 6
19.4%
3-8 3
 
9.7%
6-8 2
 
6.5%
5-8 2
 
6.5%
4-6 2
 
6.5%
4-4 2
 
6.5%
1-8 1
 
3.2%
3-6 1
 
3.2%
6-6 1
 
3.2%
Other values (3) 3
 
9.7%
2023-07-13T22:07:33.890314image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 31
33.3%
4 21
22.6%
3 12
 
12.9%
6 9
 
9.7%
8 8
 
8.6%
2 7
 
7.5%
5 3
 
3.2%
1 2
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
66.7%
Dash Punctuation 31
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 21
33.9%
3 12
19.4%
6 9
14.5%
8 8
 
12.9%
2 7
 
11.3%
5 3
 
4.8%
1 2
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 93
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 31
33.3%
4 21
22.6%
3 12
 
12.9%
6 9
 
9.7%
8 8
 
8.6%
2 7
 
7.5%
5 3
 
3.2%
1 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 31
33.3%
4 21
22.6%
3 12
 
12.9%
6 9
 
9.7%
8 8
 
8.6%
2 7
 
7.5%
5 3
 
3.2%
1 2
 
2.2%
Distinct12
Distinct (%)38.7%
Missing1602
Missing (%)98.1%
Memory size12.9 KiB
2023-07-13T22:07:33.980628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters93
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row5-8
2nd row2-8
3rd row4-8
4th row6-8
5th row6-8
ValueCountFrequency (%)
2-4 8
25.8%
3-4 4
12.9%
3-6 3
 
9.7%
1-4 3
 
9.7%
5-8 2
 
6.5%
2-8 2
 
6.5%
6-8 2
 
6.5%
4-6 2
 
6.5%
4-4 2
 
6.5%
4-8 1
 
3.2%
Other values (2) 2
 
6.5%
2023-07-13T22:07:34.115781image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 31
33.3%
4 22
23.7%
2 10
 
10.8%
6 8
 
8.6%
8 8
 
8.6%
3 7
 
7.5%
1 3
 
3.2%
5 3
 
3.2%
7 1
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
66.7%
Dash Punctuation 31
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 22
35.5%
2 10
16.1%
6 8
 
12.9%
8 8
 
12.9%
3 7
 
11.3%
1 3
 
4.8%
5 3
 
4.8%
7 1
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 93
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 31
33.3%
4 22
23.7%
2 10
 
10.8%
6 8
 
8.6%
8 8
 
8.6%
3 7
 
7.5%
1 3
 
3.2%
5 3
 
3.2%
7 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 31
33.3%
4 22
23.7%
2 10
 
10.8%
6 8
 
8.6%
8 8
 
8.6%
3 7
 
7.5%
1 3
 
3.2%
5 3
 
3.2%
7 1
 
1.1%

on_move_fifteen
Text

MISSING 

Distinct122
Distinct (%)66.3%
Missing1449
Missing (%)88.7%
Memory size12.9 KiB
2023-07-13T22:07:34.368879image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.847826087
Min length3

Characters and Unicode

Total characters892
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)42.4%

Sample

1st row21-35
2nd row19-30
3rd row21-37
4th row18-36
5th row22-36
ValueCountFrequency (%)
23-34 5
 
2.7%
22-32 4
 
2.2%
7-11 4
 
2.2%
23-36 4
 
2.2%
19-31 4
 
2.2%
15-30 4
 
2.2%
23-39 3
 
1.6%
22-33 3
 
1.6%
20-32 3
 
1.6%
18-29 3
 
1.6%
Other values (112) 147
79.9%
2023-07-13T22:07:34.683441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 184
20.6%
2 176
19.7%
3 163
18.3%
1 116
13.0%
9 45
 
5.0%
4 39
 
4.4%
0 38
 
4.3%
5 35
 
3.9%
8 35
 
3.9%
6 33
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 708
79.4%
Dash Punctuation 184
 
20.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 176
24.9%
3 163
23.0%
1 116
16.4%
9 45
 
6.4%
4 39
 
5.5%
0 38
 
5.4%
5 35
 
4.9%
8 35
 
4.9%
6 33
 
4.7%
7 28
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 892
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 184
20.6%
2 176
19.7%
3 163
18.3%
1 116
13.0%
9 45
 
5.0%
4 39
 
4.4%
0 38
 
4.3%
5 35
 
3.9%
8 35
 
3.9%
6 33
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 892
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 184
20.6%
2 176
19.7%
3 163
18.3%
1 116
13.0%
9 45
 
5.0%
4 39
 
4.4%
0 38
 
4.3%
5 35
 
3.9%
8 35
 
3.9%
6 33
 
3.7%

on_move_college
Text

MISSING 

Distinct57
Distinct (%)33.9%
Missing1465
Missing (%)89.7%
Memory size12.9 KiB
2023-07-13T22:07:34.856384image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.821428571
Min length3

Characters and Unicode

Total characters810
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)21.4%

Sample

1st row12-30
2nd row19-36
3rd row28-34
4th row26-34
5th row30-48
ValueCountFrequency (%)
12-25 19
 
11.3%
11-25 14
 
8.3%
14-25 14
 
8.3%
13-25 12
 
7.1%
15-25 12
 
7.1%
16-25 12
 
7.1%
17-25 8
 
4.8%
10-25 7
 
4.2%
9-25 6
 
3.6%
19-25 4
 
2.4%
Other values (47) 60
35.7%
2023-07-13T22:07:35.084012image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 168
20.7%
2 166
20.5%
1 155
19.1%
5 135
16.7%
4 43
 
5.3%
3 35
 
4.3%
6 30
 
3.7%
7 23
 
2.8%
9 19
 
2.3%
0 18
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 642
79.3%
Dash Punctuation 168
 
20.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 166
25.9%
1 155
24.1%
5 135
21.0%
4 43
 
6.7%
3 35
 
5.5%
6 30
 
4.7%
7 23
 
3.6%
9 19
 
3.0%
0 18
 
2.8%
8 18
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 810
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 168
20.7%
2 166
20.5%
1 155
19.1%
5 135
16.7%
4 43
 
5.3%
3 35
 
4.3%
6 30
 
3.7%
7 23
 
2.8%
9 19
 
2.3%
0 18
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 810
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 168
20.7%
2 166
20.5%
1 155
19.1%
5 135
16.7%
4 43
 
5.3%
3 35
 
4.3%
6 30
 
3.7%
7 23
 
2.8%
9 19
 
2.3%
0 18
 
2.2%